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Essays on empirical asset pricing

Chen, Huaizhi (2015) Essays on empirical asset pricing. PhD thesis, London School of Economics and Political Science.

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Identification Number: 10.21953/lse.ar7jcg8wo0j6


My thesis consists of three papers on empirical asset pricing. The first two papers explore the ways through which mutual fund companies impact the market. The last one explores a strategic behavior of firms toward investors. In my first paper, I examine the price impact of portfolio balancing by professional investment managers. I find that asset managers tend to rebalance their portfolios seasonally, adjusting around the earnings announcement periods of the underlying, and in turn causing fluctuations in the cross section of assets beyond those documented in the literature. The asset management industry trades more with outside market participants during the earnings season than the rest of the quarter. Consequently, these trades have price impact and generate a seasonal variation in Momentum returns across the cross section of equities. The second paper explores the intermediation of profits by asset managers to investors. Asset managers distribute capital gains and dividends at fixed dates even though the accrual of gains and dividends occur throughout the year. I exploit this staggered nature of capital distribution in asset intermediation to study the influence of institutional money management on asset prices. These results indicate that institutional structures contribute to the daily variation of stock market returns and that manager preference has significant impact over the co-movement of his managed assets. My third paper is joint work with Dong Lou and Lauren Cohen. We explore a mechanism through which investors take correlated shortcuts, and present strong evidence that firm managers undertake actions in response to these shortcuts. Specifically, we exploit a regulatory provision governing firm classification into industries, wherein a firm’s primary industry is determined by the segment with the highest sales. We find that investors overly rely on this classification: Firms just above the industry classification cutoff have significantly higher betas with respect to that industry.

Item Type: Thesis (PhD)
Additional Information: © 2015 Huaizhi Chen
Library of Congress subject classification: H Social Sciences > HG Finance
Sets: Departments > Finance
Supervisor: Polk, Christopher and Lou, Dong

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